CoEx

Abstract

Application-Specific Instruction Set Processors (ASIPs) provide the adequate performance/efficiency tradeoff for their particular application domain. Nevertheless, their design methodologies have stagnated during the past decade and are still based on a series of manual and time-consuming iterative steps. Furthermore, there exists a productivity gap between the point where an application is given as the target for processor customization and the time a customized architecture is available. Therefore, new tools are required that reduce the number of design iterations and bridge the aforementioned productivity gap. This can be achieved by (1) profiling technologies that, by adapting to the designer’s needs, help to gain insight into application specifications, and (2) prearchitectural design technologies that give early yet accurate feedback on the impact of algorithmic/architectural design decisions. The first requirement is addressed in this article by proposing the multigrained profiling approach, which identifies the profiling needs at each step of ASIP design and lets the designer tailor the level of detail for application inspection. CoEx, a practical implementation of the approach, is also introduced. The second requirement is addressed by creating a prearchitectural estimation engine . This engine couples CoEx reports for an application with an abstract processor model and generates an estimate of the achievable performance. Both CoEx and the performance estimation engine are respectively evaluated for instrumentation-induced execution overhead and accuracy. Finally, the development of an ASIP architecture for an augmented reality computer vision application is presented. The ASIP achieves a gain of six times compared to the original application performance, after being developed in only 2 days.